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Related Experiment Video

Updated: May 25, 2026

Quantification of Optic Nerve Cross Sectional Area on MRI: A Novel Protocol using Fiji Software
08:57

Quantification of Optic Nerve Cross Sectional Area on MRI: A Novel Protocol using Fiji Software

Published on: September 4, 2021

Model-based optic nerve head segmentation on retinal fundus images.

Fengshou Yin1, Jiang Liu, Sim Heng Ong

  • 1Institute for Infocomm Research, A*STAR, Singapore. fyin@ i2r.a-star.edu.sg

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
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Accurate optic disc detection in retinal images is crucial for diagnosing eye diseases. Our new method precisely locates and segments the optic disc, improving computer-aided diagnosis systems.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Computer Vision

Background:

  • The optic nerve head (optic disc) is vital for diagnosing retinal diseases.
  • Accurate optic disc localization and segmentation are essential for developing effective computer-aided diagnosis (CAD) systems.

Purpose of the Study:

  • To propose and evaluate a novel method for automatic optic disc detection in retinal fundus images.
  • To enhance the performance of computer-aided diagnosis systems for retinal diseases.

Main Methods:

  • The proposed method integrates edge detection, the Circular Hough Transform, and a statistical deformable model.
  • The algorithm was tested on a dataset comprising 325 digital color fundus images, including normal and pathological cases.

Main Results:

Related Experiment Videos

Last Updated: May 25, 2026

Quantification of Optic Nerve Cross Sectional Area on MRI: A Novel Protocol using Fiji Software
08:57

Quantification of Optic Nerve Cross Sectional Area on MRI: A Novel Protocol using Fiji Software

Published on: September 4, 2021

  • The system achieved an average area overlap error of 11.3% and an average absolute area error of 10.8%.
  • Performance metrics indicate superior results compared to existing optic disc detection methods.
  • A high correlation with ground truth segmentation was observed.

Conclusions:

  • The developed method demonstrates high accuracy in optic disc localization and segmentation.
  • The system shows significant potential for integration into broader retinal computer-aided diagnosis frameworks.
  • This advancement can improve the efficiency and reliability of diagnosing retinal diseases.